Kanchana, S (2022) Empirical Investigation for Predicting Depression from Different Machine Learning Based Voice Recognition Techniques. Evidence-Based Complementary and Alternative Medicine Volume 2022, Article ID , 9: 6395860. pp. 1-9.

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Abstract

Over the past few decades, the rate of diagnosing depression and mental illness among youths in both genders has been emerging
as a challenging issue in the present society. Adequate numbers of cases that have been prevailing had unheard of symptoms linked
to mental depression that are able to be detected using their voice recordings and their messages in social media websites. Due to
the wide spread usage of mobile phones, services and social sites emotion prediction and analyzing have been an indispensable
part of providing vital care for the eminence of youth’s life. In addition to dynamicity and popularity of mobile applications and
services, it is really a challenge to provide an emotion prediction system that can collect, analyze, and process emotional
communications in real time and as well as in a highly accurate manner with minimal computation time. Few depression
prediction researchers have analyzed and examined that various social networking sites and its activities may be merged to low
self-confidence, particularly in young people and adolescents. Moreover, the researchers suggest that several objective voice
acoustic measures affected by depression can be detected reliably over the smart phones. And also in some observational study, it is
stated that speech samples of patients from the telephone were obtained each week using an IVR system, and voice recording files
from smart phones have been under process for predicting the depression. Such that several telephonic standards for obtaining
voice data were identified as a crucial factor influencing the reliability and eminence of speech data. Hence, this article investigates
on different process applied in different machine learning algorithms in recognizing voice signals which in turn will be used for
scrutinizing the techniques for detecting depression levels in future. %is will make a blooming change in the youth’s life and solve
the social unethical issues in hand.

Item Type: Article
Depositing User: Mr Team Mosys
Date Deposited: 27 Sep 2022 05:12
Last Modified: 27 Sep 2022 05:12
URI: http://ir.psgcas.ac.in/id/eprint/1552

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